Multi-Model AI Comparator (2-4 Models)
Compare any 2 to 4 frontier AI models side by side across Intelligence Index, coding & reasoning benchmarks, API token pricing, context window, and inference speed.
Multi-Model Benchmark & Official Release Intelligence Matrix
Compare Up to 5 AI Models Side-by-Side on One Page
Evaluate benchmark scores, token pricing, speed, and official provider release specs (API Model ID, Rate Limits, Computer Use, MCP, VRAM & ZDR Compliance) side by side.
2 / 5 Models Active
1-Click Preset Multi-Model Stacks (4 Models):
Currently Compared Models:Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B Arena
Intelligence vs Blended Price (7:2:1)
Top-left quadrant delivers the highest intelligence per dollar
Intelligence vs Output Speed (tok/s)
Top-right quadrant delivers both frontier intelligence and real-time throughput
| Benchmark / Official Specification | NVIDIA · 2026-04 | NVIDIA · 2026-03 |
|---|---|---|
| 1. Official Benchmarks & Capability Scores (Green = Leader) | ||
| Intelligence Index (Composite) | 48 / 100 | 53 / 100 |
| SWE-bench Verified (Agentic Coding) | 42% | 51% |
| GPQA Diamond (PhD-Level Science) | 56.5% | 64.5% |
| LiveCodeBench (Competitive Coding) | N/A | N/A |
| AIME (Olympiad Competition Math) | 66% | 74% |
| MMLU-Pro (10-Choice Reasoning) | 77.2% | 82.8% |
| HumanEval (Code Synthesis) | 87.5% | 91.5% |
| Terminal-Bench (Agentic CLI Execution) | 36.5% | 45% |
| LMSYS Chatbot Arena Elo | 1310 | 1350 |
| 2. Token Pricing, Prompt Cache & Throughput Speed | ||
| Input Price (per 1M tokens) | $0.20 / 1M | $0.30 / 1M |
| Output Price (per 1M tokens) | $0.60 / 1M | $0.80 / 1M |
| Cached Input Price (per 1M tokens) | $0.050 / 1M | $0.060 / 1M |
| Blended Price (7:2:1 Cached Workload) | $0.14 / 1M | $0.18 / 1M |
| Context Window Capacity | 256K tokens | 262K tokens |
| Max Output Tokens | 16K tokens | 33K tokens |
| Output Speed (Tokens / sec) | 105 tok/s | 85 tok/s |
| Time to First Token (TTFT Latency) | 0.38s (380 ms) | 0.46s (460 ms) |
| 3. Official Provider Release Specs, API Quotas & Long-Context Rules | ||
| Official API Model ID (SDK) | nemotron-3-nano-omni-30b-a3b | nemotron-3-super-120b-a12b |
| API Protocol & Endpoint | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Lifecycle & GA Support Window | Active GA (Guaranteed support through 2028+) | Active GA (Guaranteed support through 2028+) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.2/1M in) across full 256K window | Flat rate ($0.3/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.06/1M tokens |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) |
| 4. Agentic Capabilities, Self-Hosting VRAM & Enterprise Compliance | ||
| Computer Use / Browser GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Code Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 74 GB VRAM (4-bit Quantized) · 258 GB VRAM (Native BF16) |
| Supported Inference Engines | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Architecture & Weights License | Omnimodal Sparse MoE (30B Total / 3B Active) · Open Weights (Self-Hostable) | High-Throughput Sparse MoE (120B Total / 12B Active) · Open Weights (Self-Hostable) |
Interactive AI Model Comparator
Compare Any Two AI Models Head-to-Head
Select any two models across 33 global AI labs (Google, OpenAI, Anthropic, xAI, Meta, DeepSeek, Alibaba Qwen, Mistral & more) to evaluate token economics, speed, benchmarks, and context.
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.